scispace - formally typeset
Search or ask a question
Topic

Structural health monitoring

About: Structural health monitoring is a research topic. Over the lifetime, 11727 publications have been published within this topic receiving 186231 citations.


Papers
More filters
Journal ArticleDOI
TL;DR: A bridge monitoring TestBed is developed as a research environment for sensor networks and related decision-support technologies, thereby providing accurate time synchronization between the response and corresponding traffic loads.
Abstract: A bridge monitoring TestBed is developed as a research environment for sensor networks and related decision-support technologies. A continuous monitoring system, capable of handling a large number of sensor data channels and three video signals, is deployed on a four-span, 90-m long, reinforced concrete highway bridge. Of interest is the integration of the image and sensor data acquisition into a single computer, thereby providing accurate time synchronization between the response and corresponding traffic loads. Currently, video and acceleration records corresponding to traffic induced vibration are being recorded. All systems operate online via a high-speed wireless Internet network, allowing real-time data transmission. Elements of the above health monitoring framework are presented herein. Integration of these elements into an automated functional system is emphasized. The recorded data are currently being employed for structural system identification via a model-free technique. Effort is also underway to correlate the moving traffic loads with the recorded accelerations. Finally, the TestBed is available as a resource for verification of new sensor technologies, data acquisition/ transmission algorithms, data mining strategies, and for decision-support applications.

103 citations

Book ChapterDOI
TL;DR: can be found at: Structural Health Monitoring Additional services and information for http://shm.sagepub.com/subscriptions.
Abstract: can be found at: Structural Health Monitoring Additional services and information for http://shm.sagepub.com/cgi/alerts Email Alerts: http://shm.sagepub.com/subscriptions Subscriptions: http://www.sagepub.com/journalsReprints.nav Reprints: http://www.sagepub.com/journalsPermissions.nav Permissions: http://shm.sagepub.com/cgi/content/refs/2/3/257 SAGE Journals Online and HighWire Press platforms): (this article cites 14 articles hosted on the Citations

103 citations

Journal ArticleDOI
TL;DR: An overview of emerging wireless sensor networks (WSN) for autonomous SHM systems, their application, the power use and sources needed to support autonomy, and the type of communication that allows remote monitoring are given.
Abstract: Aging and degradation of transportation infrastructure pose significant safety concerns, especially in light of increased use of these structures. The economic downturn further exacerbates such concerns, especially for critical structures such as bridges, where replacement is infeasible and maintenance and repair are expensive. The US Federal Highway Administration has classified over 25% of the bridges in the United States as either structurally deficient or functionally obsolete, underscoring the importance of structural health monitoring (SHM) to ensure public safety. We give an overview of emerging wireless sensor networks (WSN) for autonomous SHM systems, their application, the power use and sources needed to support autonomy, and the type of communication that allows remote monitoring.

103 citations

Journal ArticleDOI
TL;DR: The Hilbert–Huang transform is used for the extraction of new relevant damage descriptor to be adopted for Acoustic Emission (AE) pattern recognition in order to help understanding the damage process.

103 citations

Journal ArticleDOI
05 Sep 2018-Sensors
TL;DR: An innovative SHM solution through the combination of the EMI-PZT and CNN, yielding a 100% hit rate which outperforms other SHM approaches and needs only a small dataset for training the CNN, providing several advantages for industrial applications.
Abstract: Preliminaries convolutional neural network (CNN) applications have recently emerged in structural health monitoring (SHM) systems focusing mostly on vibration analysis However, the SHM literature shows clearly that there is a lack of application regarding the combination of PZT-(lead zirconate titanate) based method and CNN Likewise, applications using CNN along with the electromechanical impedance (EMI) technique applied to SHM systems are rare To encourage this combination, an innovative SHM solution through the combination of the EMI-PZT and CNN is presented here To accomplish this, the EMI signature is split into several parts followed by computing the Euclidean distances among them to form a RGB (red, green and blue) frame As a result, we introduce a dataset formed from the EMI-PZT signals of 720 frames, encompassing a total of four types of structural conditions for each PZT In a case study, the CNN-based method was experimentally evaluated using three PZTs glued onto an aluminum plate The results reveal an effective pattern classification; yielding a 100% hit rate which outperforms other SHM approaches Furthermore, the method needs only a small dataset for training the CNN, providing several advantages for industrial applications

103 citations


Network Information
Related Topics (5)
Finite element method
178.6K papers, 3M citations
82% related
Fracture mechanics
58.3K papers, 1.3M citations
79% related
Compressive strength
64.4K papers, 1M citations
78% related
Stress (mechanics)
69.5K papers, 1.1M citations
77% related
Numerical analysis
52.2K papers, 1.2M citations
77% related
Performance
Metrics
No. of papers in the topic in previous years
YearPapers
2023600
20221,374
2021776
2020746
2019803
2018708